This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Measurement of in vivo metabolism has outstanding potential for the diagnosis and monitoring of cancer, because metabolism accurately reports the tumor's biological state. An ongoing challenge in cancer imaging is to increase the number of biological features that can be viewed in vivo and correlated with tumor growth, genetics, or response to therapy. So far, "metabolic imaging" in cancer has been limited to snapshots of nutrient uptake (e.g. FDG-PET) and steady-state levels of a few abundant metabolites like lactate and choline (magnetic resonance spectroscopy). In principle, imaging based on nuclear magnetic resonance (NMR) could significantly widen the view of tumor metabolism because it would allow the user to observe the transfer of 13C from labeled probes to products by enzymatic reactions in live tissue. NMR can be integrated with MRI-based imaging to map metabolic activities to precise anatomic locations, including tumors. The major obstacle to extending NMR spectroscopy into clinical practice is the low abundance and sensitivity of the 13C nuclear spin, resulting in a low signal-to-noise ratio. Recently, however, the advent of dynamic nuclear polarization ("hyperpolarization") has drastically increased the feasibility of real-time, NMR-based imaging of metabolism in vivo. In this technique, polarization of the 13C nuclear spin state is greatly enhanced by transfer from the high spin polarization of an unpaired electron from a free radical. Although transient, this gain in polarization translates into a 10,000-fold (or greater) improvement in signal-to-noise ratio. We hypothesize that hyperpolarization of naturally-occurring metabolites like pyruvate will enable us to monitor the metabolism of live tumors in animal models of cancer. The major goal of the project is to develop methods to obtain high-resolution images of metabolic activity in tumor-bearing mice. The proposal draws on our experience using stable isotope methods to study tumor metabolism and using hyperpolarization to monitor metabolic activity in isolated cells and perfused organs. The proposed activities are the next logical step towards our goal of developing hyperpolarization as a clinical tool for diagnosing human cancer and monitoring its response to therapy. This project will benefit from concurrent activities within the Research Resource. The proposed experiments will cover the three major categories of mouse models of tumor growth: subcutaneous xenografts, tumors implanted at an orthotopic site, and a transgenic model of tumorigenesis. There are three aims: 1) Image pyruvate metabolism in subcutaneous tumors derived from cancer cell lines. 2) image pyruvate metabolism in orthotopic gliomas, and 3) image pyruvate metabolism in a mouse model of spontaneous breast cancer.